Local polynomial regression estimation of trawl size selectivity parameters using genetic algorithm

dc.contributor.authorJoshy, C.G.
dc.contributor.authorBalakrishna, N.
dc.contributor.authorMadhu, V.R.
dc.date.accessioned2019-08-24T07:04:42Z
dc.date.available2019-08-24T07:04:42Z
dc.date.issued2018
dc.description.abstractThis study used a local polynomial generalised linear model to estimate the trawl selectivity curve and its parameters. This modeling technique was applied to trawl selectivity data obtained from the codend selectivity studies of the Dussumier’s anchovy Thryssa dussumieri, an important trawl resource along the Gujarat coast, India, for 40 mm diamond and square mesh codends. The results of this model were compared with the results obtained from the parametric approach and found to have a superior fit based on the model performance statistics. Genetic algorithm was used to estimate the trawl selectivity parameters by minimising the objective function, i.e., estimated squared distance from target. The nonparametric approach was used to estimate the trawl selectivity parameter values (L50 and SR) for two species viz., Upeneus moluccensis and Trichiurus lepturus to confirm its superiority over the parametric approach.en_US
dc.identifier.citationIndian J. Fish 65(3):25-32en_US
dc.identifier.urihttp://drs.cift.res.in/handle/123456789/4209
dc.language.isoenen_US
dc.titleLocal polynomial regression estimation of trawl size selectivity parameters using genetic algorithmen_US
dc.typeArticleen_US
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